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从暴露到不良结局的分子途径重建的代谢物分析中的分析方面。

Analytical aspects of meet-in-metabolite analysis for molecular pathway reconstitution from exposure to adverse outcome.

机构信息

State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 361102, Xiamen, PR China.

State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, 361102, Xiamen, PR China.

出版信息

Mol Aspects Med. 2022 Oct;87:101006. doi: 10.1016/j.mam.2021.101006. Epub 2021 Jul 23.

Abstract

To explore the etiology of diseases is one of the major goals in epidemiological study. Meet-in-metabolite analysis reconstitutes biomonitoring-based adverse outcome (AO) pathways from environmental exposure to a disease, in which the chemical exposome-related metabolism responses are transmitted to incur the AO-related metabolism phenotypes. However, the ongoing data-dependent acquisition of non-targeted biomonitoring by high-resolution mass spectrometry (HRMS) is biased against the low abundance molecules, which forms the major of molecular internal exposome, i.e., the totality of trace levels of environmental pollutants and/or their metabolites in human samples. The recent development of data-independent acquisition protocols for HRMS screening has opened new opportunities to enhance unbiased measurement of the extremely low abundance molecules, which can encompass a wide range of analytes and has been applied in metabolomics, DNA, and protein adductomics. In addition, computational MS for small molecules is urgently required for the top-down exposome databases. Although a holistic analysis of the exposome and endogenous metabolites is plausible, multiple and flexible strategies, instead of "putting one thing above all" are proposed.

摘要

探索疾病的病因是流行病学研究的主要目标之一。代谢组学分析从环境暴露到疾病重建了基于生物监测的不良结局(AO)途径,其中与化学暴露组相关的代谢反应被传递以引发与 AO 相关的代谢表型。然而,通过高分辨率质谱(HRMS)进行的基于数据的非靶向生物监测的持续数据采集偏向于低丰度分子,这些分子构成了分子内部暴露组的主要部分,即人类样本中痕量水平的环境污染物及其代谢物的总和。最近,用于 HRMS 筛选的数据非依赖性采集协议的发展为增强对极低丰度分子的无偏测量开辟了新的机会,这些分子可以涵盖广泛的分析物,并已应用于代谢组学、DNA 和蛋白质加合物组学。此外,小分子的计算 MS 对于自上而下的暴露组数据库是急需的。虽然对暴露组和内源性代谢物进行整体分析是合理的,但建议采用多种和灵活的策略,而不是“一揽子处理”。

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